A bstract Recent advancements in deep learning models have significantly enhanced jet
classification performance by analyzing low-level features (LLFs). However, this approach …

In this paper, we present a framework for multiscale topology optimization of fluid-flow
devices. The objective is to minimize dissipated power, subject to a desired contact-area …

Physics-informed neural network (PINN) is a neural network that combines machine
learning methods with the physics of the problem often expressed in terms of differential …

The spatial display of clustered data using machine learning (ML) as regions (bordered
areas) is currently unfeasible. This problem is commonly encountered in various research …

This study presents an approach to enhance human–machine collaboration in autonomous
ship trajectory planning. A decision support system is developed, considering crucial …

Smart sensors have become pervasive in railway transportation applications, particularly in
Europe where digital technologies are increasingly being applied to the railway signaling …

Cities are increasingly prone to urban flooding due to heavier rainfall, denser populations,
augmenting imperviousness, and infrastructure aging. Urban pluvial flooding causes …

Abstract Wurm & Hattori's Language Atlas of the Pacific Area describes the geographic
speaker areas of the languages and language varieties spoken in the Pacific. Thanks to the …

Direct geological information in Antarctica is limited to ice free regions along the coast, high
mountain ranges, or isolated nunataks. Therefore, indirect methods are required to reveal …

In this paper, we present a framework for multiscale topology optimization of fluid flow
devices. The objective is to minimize dissipated power, subject to a desired contact area …